# Buggy code
def _tile_with_tensor(cls, op):
    out = op.outputs[0]
    axis = op.axis

    rhs_is_tensor = isinstance(op.rhs, TENSOR_TYPE)
    tensor, other = (op.rhs, op.lhs) if rhs_is_tensor else (op.lhs, op.rhs)
    if tensor.shape == other.shape:
        tensor = tensor.rechunk(other.nsplits)._inplace_tile()
    else:
        # shape differs only when dataframe add 1-d tensor, we need rechunk on columns axis.
        if op.axis in ["columns", 1] and other.ndim == 1:
            # force axis == 0 if it's Series other than DataFrame
            axis = 0
        rechunk_size = (
            other.nsplits[1] if axis == "columns" or axis == 1 else other.nsplits[0]
        )
        if tensor.ndim > 0:
            tensor = tensor.rechunk((rechunk_size,))._inplace_tile()

    cum_splits = [0] + np.cumsum(other.nsplits[axis]).tolist()
    out_chunks = []
    for out_index in itertools.product(*(map(range, other.chunk_shape))):
        tensor_chunk = tensor.cix[out_index[: tensor.ndim]]
        other_chunk = other.cix[out_index]
        out_op = op.copy().reset_key()
        inputs = (
            [other_chunk, tensor_chunk]
            if rhs_is_tensor
            else [tensor_chunk, other_chunk]
        )
        if isinstance(other_chunk, DATAFRAME_CHUNK_TYPE):
            start = cum_splits[out_index[axis]]
            end = cum_splits[out_index[axis] + 1]
            chunk_dtypes = out.dtypes.iloc[start:end]
            out_chunk = out_op.new_chunk(
                inputs,
                shape=other_chunk.shape,
                index=other_chunk.index,
                dtypes=chunk_dtypes,
                index_value=other_chunk.index_value,
                columns_value=other.columns_value,
            )
        else:
            out_chunk = out_op.new_chunk(
                inputs,
                shape=other_chunk.shape,
                index=other_chunk.index,
                dtype=out.dtype,
                index_value=other_chunk.index_value,
                name=other_chunk.name,
            )
        out_chunks.append(out_chunk)

    new_op = op.copy()
    if isinstance(other, SERIES_TYPE):
        return new_op.new_seriess(
            op.inputs,
            other.shape,
            nsplits=other.nsplits,
            dtype=out.dtype,
            index_value=other.index_value,
            chunks=out_chunks,
        )
    else:
        return new_op.new_dataframes(
            op.inputs,
            other.shape,
            nsplits=other.nsplits,
            dtypes=out.dtypes,
            index_value=other.index_value,
            columns_value=other.columns_value,
            chunks=out_chunks,
        )


# Traceback (TypeError)
Traceback (most recent call last):
File "/Users/wenjun.swj/miniconda3/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 3417, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-9-60fd09690beb>", line 1, in <module>
df[df[0] > 0.5].execute()
File "/Users/wenjun.swj/Code/mars/mars/core.py", line 643, in execute
return run()
File "/Users/wenjun.swj/Code/mars/mars/core.py", line 639, in run
self.data.execute(session, **kw)
File "/Users/wenjun.swj/Code/mars/mars/core.py", line 379, in execute
return run()
File "/Users/wenjun.swj/Code/mars/mars/core.py", line 374, in run
session.run(self, **kw)
File "/Users/wenjun.swj/Code/mars/mars/session.py", line 505, in run
result = self._sess.run(*tileables, **kw)
File "/Users/wenjun.swj/Code/mars/mars/session.py", line 111, in run
res = self._executor.execute_tileables(tileables, **kw)
File "/Users/wenjun.swj/Code/mars/mars/utils.py", line 451, in _inner
return func(*args, **kwargs)
File "/Users/wenjun.swj/Code/mars/mars/executor.py", line 860, in execute_tileables
chunk_graph = chunk_graph_builder.build(
File "/Users/wenjun.swj/Code/mars/mars/utils.py", line 451, in _inner
return func(*args, **kwargs)
File "/Users/wenjun.swj/Code/mars/mars/tiles.py", line 347, in build
chunk_graph = super().build(
File "/Users/wenjun.swj/Code/mars/mars/utils.py", line 451, in _inner
return func(*args, **kwargs)
File "/Users/wenjun.swj/Code/mars/mars/tiles.py", line 262, in build
self._on_tile_failure(tileable_data.op, exc_info)
File "/Users/wenjun.swj/Code/mars/mars/tiles.py", line 301, in inner
raise exc_info[1].with_traceback(exc_info[2]) from None
File "/Users/wenjun.swj/Code/mars/mars/tiles.py", line 242, in build
tiled = self._tile(tileable_data, tileable_graph)
File "/Users/wenjun.swj/Code/mars/mars/tiles.py", line 337, in _tile
return super()._tile(tileable_data, tileable_graph)
File "/Users/wenjun.swj/Code/mars/mars/tiles.py", line 201, in _tile
tds[0]._inplace_tile()
File "/Users/wenjun.swj/Code/mars/mars/core.py", line 168, in _inplace_tile
return handler.inplace_tile(self)
File "/Users/wenjun.swj/Code/mars/mars/tiles.py", line 136, in inplace_tile
dispatched = self.dispatch(to_tile.op)
File "/Users/wenjun.swj/Code/mars/mars/utils.py", line 451, in _inner
return func(*args, **kwargs)
File "/Users/wenjun.swj/Code/mars/mars/tiles.py", line 119, in dispatch
tiled = op_cls.tile(op)
File "/Users/wenjun.swj/Code/mars/mars/dataframe/indexing/getitem.py", line 273, in tile
return cls.tile_with_mask(op)
File "/Users/wenjun.swj/Code/mars/mars/dataframe/indexing/getitem.py", line 287, in tile_with_mask
align_dataframe_series(in_df, mask, axis='index')
File "/Users/wenjun.swj/Code/mars/mars/dataframe/align.py", line 713, in align_dataframe_series
index_splits, index_nsplits = _calc_axis_splits(left.index_value, right.index_value,
File "/Users/wenjun.swj/Code/mars/mars/dataframe/align.py", line 490, in _calc_axis_splits
right_splits = left_splits = [[c] for c in left_chunk_index_min_max]
TypeError: 'NoneType' object is not iterable

# Fixed code
def _tile_with_tensor(cls, op):
    out = op.outputs[0]
    axis = op.axis
    if axis is None:
        axis = 0

    rhs_is_tensor = isinstance(op.rhs, TENSOR_TYPE)
    tensor, other = (op.rhs, op.lhs) if rhs_is_tensor else (op.lhs, op.rhs)
    if tensor.shape == other.shape:
        tensor = tensor.rechunk(other.nsplits)._inplace_tile()
    else:
        # shape differs only when dataframe add 1-d tensor, we need rechunk on columns axis.
        if axis in ["columns", 1] and other.ndim == 1:
            # force axis == 0 if it's Series other than DataFrame
            axis = 0
        rechunk_size = (
            other.nsplits[1] if axis == "columns" or axis == 1 else other.nsplits[0]
        )
        if tensor.ndim > 0:
            tensor = tensor.rechunk((rechunk_size,))._inplace_tile()

    cum_splits = [0] + np.cumsum(other.nsplits[axis]).tolist()
    out_chunks = []
    for out_index in itertools.product(*(map(range, other.chunk_shape))):
        tensor_chunk = tensor.cix[out_index[: tensor.ndim]]
        other_chunk = other.cix[out_index]
        out_op = op.copy().reset_key()
        inputs = (
            [other_chunk, tensor_chunk]
            if rhs_is_tensor
            else [tensor_chunk, other_chunk]
        )
        if isinstance(other_chunk, DATAFRAME_CHUNK_TYPE):
            start = cum_splits[out_index[axis]]
            end = cum_splits[out_index[axis] + 1]
            chunk_dtypes = out.dtypes.iloc[start:end]
            out_chunk = out_op.new_chunk(
                inputs,
                shape=other_chunk.shape,
                index=other_chunk.index,
                dtypes=chunk_dtypes,
                index_value=other_chunk.index_value,
                columns_value=other.columns_value,
            )
        else:
            out_chunk = out_op.new_chunk(
                inputs,
                shape=other_chunk.shape,
                index=other_chunk.index,
                dtype=out.dtype,
                index_value=other_chunk.index_value,
                name=other_chunk.name,
            )
        out_chunks.append(out_chunk)

    new_op = op.copy()
    if isinstance(other, SERIES_TYPE):
        return new_op.new_seriess(
            op.inputs,
            other.shape,
            nsplits=other.nsplits,
            dtype=out.dtype,
            index_value=other.index_value,
            chunks=out_chunks,
        )
    else:
        return new_op.new_dataframes(
            op.inputs,
            other.shape,
            nsplits=other.nsplits,
            dtypes=out.dtypes,
            index_value=other.index_value,
            columns_value=other.columns_value,
            chunks=out_chunks,
        )