pd.Categorical.contains([item, otheritem]) raises ValueError
#### Code Sample, a copy-pastable example if possible

```python
In [2]: idx = pd.CategoricalIndex([1, 2, 3])

In [3]: list('a') in idx
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-3-76f69ba8dbb9> in <module>()
----> 1 list('a') in idx

/home/nobackup/repo/pandas/pandas/core/indexes/category.py in __contains__(self, key)
    327             return self.hasnans
    328 
--> 329         return contains(self, key, container=self._engine)
    330 
    331     @Appender(_index_shared_docs['contains'] % _index_doc_kwargs)

/home/nobackup/repo/pandas/pandas/core/arrays/categorical.py in contains(cat, key, container)
    187     before calling this method.
    188     """
--> 189     hash(key)
    190 
    191     # get location of key in categories.

TypeError: unhashable type: 'list'

In [4]: list('ab') in idx
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-4-0b6b309a5156> in <module>()
----> 1 list('ab') in idx

/home/nobackup/repo/pandas/pandas/core/indexes/category.py in __contains__(self, key)
    324     def __contains__(self, key):
    325         # if key is a NaN, check if any NaN is in self.
--> 326         if isna(key):
    327             return self.hasnans
    328 

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
```

#### Problem description

This is the only case, to the best of my (very limited - I didn't investigate much) knowledge, in which the ``contains`` method of an index raises anything different from ``TypeError: unhashable type:...``.

xref #21313

#### Expected Output

``TypeError: unhashable type: 'list'``

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit: 2b136054db3b8f4c8d1aa33160c4bbe3b8ce940e
python: 3.5.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.0-6-amd64
machine: x86_64
processor: 
byteorder: little
LC_ALL: None
LANG: it_IT.UTF-8
LOCALE: it_IT.UTF-8

pandas: 0.24.0.dev0+216.g2b136054d
pytest: 3.5.0
pip: 9.0.1
setuptools: 39.2.0
Cython: 0.25.2
numpy: 1.14.3
scipy: 0.19.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: 1.5.6
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: 1.2.0dev
tables: 3.3.0
numexpr: 2.6.1
feather: 0.3.1
matplotlib: 2.2.2.post1153+gff6786446
openpyxl: 2.3.0
xlrd: 1.0.0
xlwt: 1.3.0
xlsxwriter: 0.9.6
lxml: 4.1.1
bs4: 4.5.3
html5lib: 0.999999999
sqlalchemy: 1.0.15
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.2.1
gcsfs: None


</details>
