# Buggy code
def build_split_idx_to_origin_idx(splits, increase=True):
    # splits' len is equal to the original chunk size on a specified axis,
    # splits is sth like [[(0, True, 2, True), (2, False, 3, True)]]
    # which means there is one input chunk, and will be split into 2 out chunks
    # in this function, we want to build a new dict from the out chunk index to
    # the original chunk index and the inner position, like {0: (0, 0), 1: (0, 1)}
    if not increase:
        splits = list(reversed(splits))
    out_idx = itertools.count(0)
    res = dict()
    for origin_idx, _ in enumerate(splits):
        for pos in range(len(splits[origin_idx])):
            if increase:
                o_idx = origin_idx
            else:
                o_idx = len(splits) - origin_idx - 1
            res[next(out_idx)] = o_idx, pos
    return res


# Traceback (Exception)
In [28]: df = md.DataFrame(np.random.rand(10, 2))

In [29]: df + np.random.rand(10, 2)
---------------------------------------------------------------------------
Exception                                 Traceback (most recent call last)
<ipython-input-29-4a212df011a8> in <module>
----> 1 df + np.random.rand(10, 2)

~/Documents/mars_dev/mars/mars/dataframe/utils.py in wrapper(*args, **kwargs)
613     def wrapper(*args, **kwargs):
614         try:
--> 615             return func(*args, **kwargs)
616         except NotImplementedError:
617             return NotImplemented

~/Documents/mars_dev/mars/mars/dataframe/arithmetic/add.py in add(df, other, axis, level, fill_value)
33
34 def add(df, other, axis='columns', level=None, fill_value=None):
---> 35     other = wrap_sequence(other)
36     op = DataFrameAdd(axis=axis, level=level, fill_value=fill_value, lhs=df, rhs=other)
37     return op(df, other)

~/Documents/mars_dev/mars/mars/dataframe/utils.py in wrap_sequence(seq)
606
607     if isinstance(seq, (list, tuple, np.ndarray, TENSOR_TYPE)):
--> 608         seq = Series(seq)
609     return seq
610

~/Documents/mars_dev/mars/mars/dataframe/initializer.py in __init__(self, data, index, dtype, name, copy, chunk_size, gpu, sparse)
46             series = data
47         else:
---> 48             pd_series = pd.Series(data, index=index, dtype=dtype, name=name, copy=copy)
49             series = from_pandas_series(pd_series, chunk_size=chunk_size, gpu=gpu, sparse=sparse)
50         super(Series, self).__init__(series.data)

~/miniconda3/lib/python3.7/site-packages/pandas/core/series.py in __init__(self, data, index, dtype, name, copy, fastpath)
312                     data = data.copy()
313             else:
--> 314                 data = sanitize_array(data, index, dtype, copy, raise_cast_failure=True)
315
316                 data = SingleBlockManager(data, index, fastpath=True)

~/miniconda3/lib/python3.7/site-packages/pandas/core/internals/construction.py in sanitize_array(data, index, dtype, copy, raise_cast_failure)
727     elif subarr.ndim > 1:
728         if isinstance(data, np.ndarray):
--> 729             raise Exception("Data must be 1-dimensional")
730         else:
731             subarr = com.asarray_tuplesafe(data, dtype=dtype)

Exception: Data must be 1-dimensional

# Fixed code
def build_split_idx_to_origin_idx(splits, increase=True):
    # splits' len is equal to the original chunk size on a specified axis,
    # splits is sth like [[(0, True, 2, True), (2, False, 3, True)]]
    # which means there is one input chunk, and will be split into 2 out chunks
    # in this function, we want to build a new dict from the out chunk index to
    # the original chunk index and the inner position, like {0: (0, 0), 1: (0, 1)}
    if increase is False:
        splits = list(reversed(splits))
    out_idx = itertools.count(0)
    res = dict()
    for origin_idx, _ in enumerate(splits):
        for pos in range(len(splits[origin_idx])):
            if increase is False:
                o_idx = len(splits) - origin_idx - 1
            else:
                o_idx = origin_idx
            res[next(out_idx)] = o_idx, pos
    return res