hash_pandas_object on ExtensionArray-backed Series fails with TypeError
```python
In [1]: import pandas as pd

In [2]: pd.Series
Out[2]: pandas.core.series.Series

In [4]: s = pd.Series(pd.interval_range(0, periods=10))

In [5]: pd.util.hash_pandas_object(s)
```

```pytb
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-5-1b7247db4f16> in <module>
----> 1 pd.util.hash_pandas_object(s)

~/sandbox/pandas/pandas/core/util/hashing.py in hash_pandas_object(obj, index, encoding, hash_key, categorize)
     88     elif isinstance(obj, ABCSeries):
     89         h = hash_array(obj.values, encoding, hash_key,
---> 90                        categorize).astype('uint64', copy=False)
     91         if index:
     92             index_iter = (hash_pandas_object(obj.index,

~/sandbox/pandas/pandas/core/util/hashing.py in hash_array(vals, encoding, hash_key, categorize)
    269     # we'll be working with everything as 64-bit values, so handle this
    270     # 128-bit value early
--> 271     elif np.issubdtype(dtype, np.complex128):
    272         return hash_array(vals.real) + 23 * hash_array(vals.imag)
    273

~/Envs/pandas-dev/lib/python3.7/site-packages/numpy/core/numerictypes.py in issubdtype(arg1, arg2)
    712     """
    713     if not issubclass_(arg1, generic):
--> 714         arg1 = dtype(arg1).type
    715     if not issubclass_(arg2, generic):
    716         arg2_orig = arg2

TypeError: data type not understood

In [6]: s
Out[6]:
0     (0, 1]
1     (1, 2]
2     (2, 3]
3     (3, 4]
4     (4, 5]
5     (5, 6]
6     (6, 7]
7     (7, 8]
8     (8, 9]
9    (9, 10]
dtype: interval
```

Options

1. convert to object before hashing
2. add some kind of `_hash_values` to the interface. But, how do we prevent hash collisions between similar, but different EAs? For example, the fastest hash for a `PeriodArray` would be to just hash the ordinals. But we wouldn't want the following two to hash identically (using my PeriodArray branch)

```
In [35]: pd.core.arrays.PeriodArray._from_ordinals([10, 20], freq='H')
Out[35]:
<pandas PeriodArray>
['1970-01-01 10:00', '1970-01-01 20:00']
Length: 2, dtype: period[H]

In [36]: pd.core.arrays.PeriodArray._from_ordinals([10, 20], freq='D')
Out[36]:
<pandas PeriodArray>
['1970-01-11', '1970-01-21']
Length: 2, dtype: period[D]
```

So we need to mix the dtype information in too.