BUG: to_datetime with out-of-bounds np.datetime64 and errors='ignore' doesn't return input

[MarcoGorelli]

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Reproducible Example

In [4]: to_datetime([np.datetime64('9999-01-01')], errors='ignore')[0]
Out[4]: datetime.date(9999, 1, 1)

In [5]: to_datetime([np.datetime64('9999-01-01')], errors='ignore', format='%Y-%m-%d')[0]
Out[5]: numpy.datetime64('9999-01-01')

Issue Description

The docs say that with errors='ignore', the input will be returned, but that's not happening here

Expected Behavior

Just return the input

Installed Versions

INSTALLED VERSIONS

commit : 8acd314
python : 3.8.16.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.102.1-microsoft-standard-WSL2
Version : #1 SMP Wed Mar 2 00:30:59 UTC 2022
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8

pandas : 2.0.0.dev0+1049.g8acd31495a
numpy : 1.23.5
pytz : 2022.7
dateutil : 2.8.2
setuptools : 65.6.3
pip : 22.3.1
Cython : 0.29.32
pytest : 7.2.0
hypothesis : 6.61.0
sphinx : 5.3.0
blosc : 1.11.1
feather : None
xlsxwriter : 3.0.6
lxml.etree : 4.9.2
html5lib : 1.1
pymysql : 1.0.2
psycopg2 : 2.9.5
jinja2 : 3.1.2
IPython : 8.8.0
pandas_datareader: None
bs4 : 4.11.1
bottleneck : 1.3.5
brotli :
fastparquet : 2022.12.0
fsspec : 2022.11.0
gcsfs : 2022.11.0
matplotlib : 3.6.2
numba : 0.56.4
numexpr : 2.8.4
odfpy : None
openpyxl : 3.0.10
pandas_gbq : None
pyarrow : 10.0.1
pyreadstat : 1.2.0
pyxlsb : 1.0.10
s3fs : 2022.11.0
scipy : 1.10.0
snappy :
sqlalchemy : 1.4.46
tables : 3.8.0
tabulate : 0.9.0
xarray : 2022.12.0
xlrd : 2.0.1
zstandard : 0.19.0
tzdata : 2022.7
qtpy : None
pyqt5 : None
None

[jbrockmendel]

The docs say that with errors='ignore', the input will be returned, but that's not happening here

ive been thinking about this recently w/r/t to the two helpers in tslib.pyx. I figure "ignore" means either

a) "return the input unchanged", in which case we should consider deprecating it and telling users to do try/except themselves
b) pd.to_datetime(obj, errors="ignore") on error falls back to essentiallyobj.apply(try_to_datetime_ignore_on_error). Which I have no objection to, but it's not quite what we do in the fallback-helpers.

[MarcoGorelli]

yeah my thinking is

1. fixup this inconsistency and simplify the codebase
2. deprecate

In all my Kaggle notebook scrapes I've never seen errors='ignore' anyway, the only place I've ever seen it is internally in the csv parser. We're just creating more work for ourselves with this one IMO

[jbrockmendel]

do you want to try changing this in 2.0? or deprecate in 2.x?

[MarcoGorelli]

yeah sure, I'll try to get a PR to fix the inconsistency and simplify the logic into 2.0 and then we can deprecate 'ignore' completely in 2.x