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Reproducible Example

import pandas as pd
index = pd.date_range('2023-10-28', '2023-10-30', freq='30min', tz='Europe/Vienna')
freq = '1min'

index.round(freq)  # raises: AmbiguousTimeError: Cannot infer dst time from 2023-10-29 02:00:00, try using the 'ambiguous' argument

index.tz_convert('utc').round(freq).tz_convert(index.tz) # runs without problem

index.round(freq, ambiguous='infer')  # would also work, but I don't think there is anything ambiguous since a tz is present

Issue Description

index.round(freq)

raises: AmbiguousTimeError: Cannot infer dst time from 2023-10-29 02:00:00, try using the 'ambiguous' argument.

Although I don't think there is anything ambiguous since a timezone is present.

Expected Behavior

I would expect that the 'ambiguous' argument is not needed.

Installed Versions

INSTALLED VERSIONS ------------------ commit : a60ad39b4a9febdea9a59d602dad44b1538b0ea5 python : 3.11.6.final.0 python-bits : 64 OS : Darwin OS-release : 23.1.0 Version : Darwin Kernel Version 23.1.0: Mon Oct 9 21:27:24 PDT 2023; root:xnu-10002.41.9~6/RELEASE_ARM64_T6000 machine : arm64 processor : arm byteorder : little LC_ALL : en_US.UTF-8 LANG : en_US.UTF-8 LOCALE : en_US.UTF-8 pandas : 2.1.2 numpy : 1.24.2 pytz : 2022.7.1 dateutil : 2.8.2 setuptools : 65.5.1 pip : 23.2.1 Cython : 3.0.2 pytest : None hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : 4.9.3 html5lib : None pymysql : 1.4.6 psycopg2 : None jinja2 : 3.1.2 IPython : 8.17.2 pandas_datareader : None bs4 : 4.12.2 bottleneck : None dataframe-api-compat: None fastparquet : 2023.7.0 fsspec : 2023.3.0 gcsfs : None matplotlib : 3.8.0 numba : 0.57.1 numexpr : None odfpy : None openpyxl : 3.1.2 pandas_gbq : None pyarrow : 12.0.1 pyreadstat : None pyxlsb : None s3fs : None scipy : 1.10.1 sqlalchemy : 2.0.19 tables : None tabulate : 0.9.0 xarray : 2023.8.0 xlrd : None zstandard : None tzdata : 2022.7 qtpy : None pyqt5 : None