BUG: TypeError when doing equality comparison with Extension Dtype 
### 

- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.

- [ ] I have confirmed this bug exists on the master branch of pandas.


### Reproducible Example

```python
s1 = pd.Series([1,2,3,4,5, None])
s2 = s1.astype('Int16')
s1.dtype
Out[13]: dtype('float64')

s2.dtype
Out[14]: Int16Dtype()

# Equality using extension Dtype first works as expected
s2.dtype == s1.dtype
Out[15]: False

# Equality using non-extension Dtype first raises TypeError
s1.dtype == s2.dtype

  File "<ipython-input-16-8f0ca559fe44>", line 1, in <module>
    s1.dtype == s2.dtype
TypeError: Cannot interpret 'Int16Dtype()' as a data type
```


### Issue Description

It appears that when doing a dtype comparison with a non-extension Dtype first and extension Dtype second causes TypeError, whereas doing the other way round works as expected

### Expected Behavior

Dtype comparison behaviour should not depend on the order of the dtypes in the statement

### Installed Versions

<details>

INSTALLED VERSIONS
------------------
commit           : 73c68257545b5f8530b7044f56647bd2db92e2ba
python           : 3.9.1.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.18362
machine          : AMD64
processor        : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : English_Australia.1252
pandas           : 1.3.3
numpy            : 1.20.3
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 20.2.3
setuptools       : 49.2.1
Cython           : 0.29.24
pytest           : 6.2.2
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.6.3
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 3.0.1
IPython          : 7.25.0
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.4.3
numexpr          : None
odfpy            : None
openpyxl         : 3.0.6
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : 2.0.1
xlwt             : 1.3.0
numba            : 0.54.0


</details>
