BUG: Calling tz_localize suppresses ValueError when converting from NaT to np.int64
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

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

---

#### Code Sample, a copy-pastable example

```python
import numpy as np
import pandas as pd

ser = pd.Series([pd.NaT], dtype="datetime64[ns]")
ser = ser.dt.tz_localize("America/Los_Angeles")

print(ser.astype(np.int64)[0])
```

#### Problem description
The code snippet above prints `-9223372036854775808` (-2<sup>63</sup>) instead of raising a `ValueError`, which is the behavior that would occur if `tz_localize` were not called.

#### Expected Output
Should raise a `ValueError: Cannot convert NaT values to integer`.

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

<details>


INSTALLED VERSIONS
------------------
commit           : 3e89b4c4b1580aa890023fc550774e63d499da25
python           : 3.8.5.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.8.0-36-generic
Version          : #40~20.04.1-Ubuntu SMP Wed Jan 6 10:15:55 UTC 2021
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.2.0
numpy            : 1.19.5
pytz             : 2020.5
dateutil         : 2.8.1
pip              : 20.3.3
setuptools       : 51.0.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
