BUG: Ambiguous time throws ambiguous error but then does not allow remediation with fold argument

[MataanAMZ]

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the master branch of pandas.

Reproducible Example

import pandas as pd
start_date = "2021-11-07T01:00:00"
tz = "America/Denver"
start_date = int(pd.Timestamp(start_date, tz=tz).timestamp(), fold=1)

Issue Description

The above code throws the following error.

ValueError: Cannot pass fold with possibly unambiguous input: int, float, numpy.datetime64, str, or timezone-aware datetime-like. Pass naive datetime-like or build Timestamp from components.

start_date with the tz is ambiguous, and it is a naive datetime-like.

Expected Behavior

Instead of this error, pd.Timestamp should fold the time to the second occurrence of Nov 7th 1am

Installed Versions

INSTALLED VERSIONS

commit : 945c9ed
python : 3.8.9.final.0
python-bits : 64
OS : Darwin
OS-release : 20.6.0
Version : Darwin Kernel Version 20.6.0: Mon Aug 30 06:12:21 PDT 2021; root:xnu-7195.141.6~3/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.3.4
numpy : 1.21.4
pytz : 2021.3
dateutil : 2.8.2
pip : 21.3.1
setuptools : 49.2.1
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

[mroeschke]

The pd.Timestamp(start_date, tz=tz) call is raising the error (int doesn't accept a fold argument)

Moreover, fold is only supported if the Timestamp constructor is built from components (e.g. year=2021, month=11, etc)

We recommend instead using tz_localize for better localization support during ambiguous times (e.g. Timestamp(...).tz_localize(tz, ambiguous=True/False/...etc)