inconsistent behaviour of loc when slicing on multiindex containing numpy.datetime64
#### Code Sample, a copy-pastable example if possible

```python
import pandas
import numpy

df = pandas.DataFrame({'A': list(range(6)), 'B': list(range(6))},
					  index=pandas.MultiIndex.from_product(
					  										[[numpy.datetime64('2017-10-10'), numpy.datetime64('2017-10-11')], range(3)],
					  										names=['date', 'count']),
					  )

# inconsitency 1: drop level
print(df.loc[('2017-10-10')])
print(df.loc[(numpy.datetime64('2017-10-10'))])

# inconsitency 2: DataFrame or Series
print(df.loc[('2017-10-10', 1), :])
print(df.loc[('2017-10-10', 1)])

# inconsistency 3: raises TypeError
try:
	print(df.loc[(numpy.datetime64('2017-10-10'), 1)])
except TypeError as e:
	print(e)
try:
	print(df.loc[(slice('2017-10-10'), slice(1))])
except TypeError as e:
	print(e)

# workaround
# inconsitency 1: drop level
print(df.loc[(slice('2017-10-10'))])
print(df.loc[(slice(numpy.datetime64('2017-10-10')))])

# inconsitency 2: DataFrame or Series
print(df.loc[(slice('2017-10-10'), slice(1)), :])

# inconsistency 3: raises TypeError
print(df.loc[(slice(numpy.datetime64('2017-10-10')), slice(1)), :])

```
#### Problem description

When DataFrame (or Series) has a MultiIndex containing numpy.datetime64 in one of the levels, slicing with loc shows inconsistent behaviour. I haven't tested if these inconsistencies are specific to numpy.datetime64 or if they are are also present when using other date formats.

In my view, the output format of loc should not depend on the format of the slice.

#### Expected Output

It's not up to me to decide on the correct output format but they should be equal, independent of the slice format. Ideally it's the ouput generated in the 'workaround' section.

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.2.candidate.1
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: None.None

pandas: 0.21.0
pytest: None
pip: 9.0.1
setuptools: 32.3.1
Cython: 0.26.1
numpy: 1.13.3
scipy: 1.0.0
pyarrow: None
xarray: 0.10.0
IPython: None
sphinx: None
patsy: None
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: None
tables: 3.4.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.8
xlrd: 1.0.0
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
