Timestamps with different same tzinfo but different tzinfo type (datetime.timezone vs pytz.UTC)
#### Code Sample, a copy-pastable example if possible

```python
import pytz
import datetime
import pandas as pd
date = pd.Timestamp("13-12-2020",tzinfo=datetime.timezone.utc)
date2 = pd.Timestamp("12-12-2020",tzinfo=pytz.UTC)
date - date2

>>> Traceback (most recent call last):
 File "<stdin>", line 1, in <module>
 File "pandas/_libs/tslibs/c_timestamp.pyx", line 300, in
 pandas._libs.tslibs.c_timestamp._Timestamp.__sub__
TypeError: Timestamp subtraction must have the same timezones or no timezones
```
#### Problem description
Current's timezone comparison is not timzone object type sensitive. Even if two dates are UTC but different tzinfo object (e.g: datetime.timezone.utc and pytz.UTC) they will be considered different timezones.
This could lead to unstabilitites since a Timestamp can have both obejct types as tzinfo

#### Expected Output

```python
import pytz
import datetime
import pandas as pd
date = pd.Timestamp("13-12-2020",tzinfo=datetime.timezone.utc)
date2 = pd.Timestamp("12-12-2020",tzinfo=pytz.UTC)
date - date2
>>> Timedelta('1 days 00:00:00')
```
#### Output of ``pd.show_versions()``

<details>

[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit           : None
python           : 3.6.9.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.4.0-18362-Microsoft
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : C.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.3
numpy            : 1.18.2
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 19.3.1
setuptools       : 45.0.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.1
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.2.1
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None

</details>
