BUG: pandas.DataFrame.where doesn't work when cond is of Pandas Dtype

[JeremyVriens]

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Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.

Code Sample, a copy-pastable example

import pandas as pd

df = pd.DataFrame()
df["input_col"] = ["a", "b", "c"]
df["is_valid_row"] = pd.Series([1, 1, 0], dtype="Int64")
df["output_col"] = df[["input_col"]].where(df["is_valid_row"] == 1)  # AssertionError is thrown here

Problem description

The code snippet is simplified to show that when using pandas.DataFrame.where in combination with a Pandas Dtype (Int64) an AssertionError is raised.
Note that when df["input_col"] (= pandas.Series.where) or dtype="int64" (instead of "Int64") is used, the code behaves as expected.

This behaviour is broken since Pandas >= 1.1 (still an issue in 1.1.2).

Expected Output

output_col
a
b
NaN

Output of pd.show_versions()

INSTALLED VERSIONS

commit : 2a7d332
python : 3.8.2.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.18362
machine : AMD64
processor : Intel64 Family 6 Model 85 Stepping 4, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252
pandas : 1.1.2
numpy : 1.19.2
pytz : 2020.1
dateutil : 2.8.1
pip : 20.2.3
setuptools : 46.2.0
Cython : None
pytest : 6.0.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 1.3.3
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.18.1
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
pytables : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : 1.3.19
tables : None
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : None
numba : None

[dsaxton]

Thanks @JeremyVriens, this is fixed by #36201 (also a duplicate of #35429)

[JeremyVriens]

@dsaxton thank you for the reply (and the fix)!