ENH: enable pd.cut to handle i8 convertibles
so this should work for timedeltas AND datetimes.

Should be straight forward. detect an i8 convertible. turn into i8. do the cut. turn back to the original dtype.

```
In [15]: s = Series(pd.to_timedelta(np.random.randint(0,100,size=10),unit='ms')).sort_values()

In [16]: s
Out[16]:
3   00:00:00.005000
5   00:00:00.007000
7   00:00:00.010000
4   00:00:00.017000
9   00:00:00.023000
1   00:00:00.043000
0   00:00:00.045000
6   00:00:00.047000
8   00:00:00.065000
2   00:00:00.090000
dtype: timedelta64[ns]

In [18]: pd.cut(s, 5)
TypeError: unsupported operand type(s) for +: 'Timedelta' and 'float'

# works when converted
In [17]: pd.cut(s.astype('timedelta64[ms]'), 5)
Out[17]:
3    (4.915, 22]
5    (4.915, 22]
7    (4.915, 22]
4    (4.915, 22]
9       (22, 39]
1       (39, 56]
0       (39, 56]
6       (39, 56]
8       (56, 73]
2       (73, 90]
dtype: category
Categories (5, object): [(4.915, 22] < (22, 39] < (39, 56] < (56, 73] < (73, 90]]

```