BUG: numpy nan_to_num functions not outputing DataFrames

[lcrmorin]

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Reproducible Example

import numpy as np, pandas as pd
data = pd.DataFrame([np.nan,1,2,3,np.Inf])
np.nan_to_num(data)

### Issue Description

It seems that some numpy functions applied on a pandas DataFrame output numpy arrays / pandas DataFrames inconsistently. 
As an exemple is the nan_to_num function outputting a numpy array instead of a DataFrame, while for exemple the numpy log function correctly output a DataFrame. I have asked about this issue on the numpy github and was told that it is a panda issue.  

### Expected Behavior

Ideally np.nan_to_num would output a DataFrame, one that can currently be obtained in the following way:

`pd.DataFrame(np.nan_to_num(data),index=data.index,columns=data.columns)`

### Installed Versions

I only tried this with pandas version 1.5.3, but checked the logs to see if the problem was resolved.


<details>

INSTALLED VERSIONS
------------------
commit           : 2e218d10984e9919f0296931d92ea851c6a6faf5
python           : 3.10.12.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.15.109+
Version          : #1 SMP Wed Jun 28 11:06:41 UTC 2023
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : C.UTF-8
LANG             : C.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.5.3
numpy            : 1.23.5
pytz             : 2023.3
dateutil         : 2.8.2
setuptools       : 59.8.0
pip              : 23.1.2
Cython           : 0.29.35
pytest           : 7.4.0
hypothesis       : None
sphinx           : None
blosc            : None
feather          : 0.4.1
xlsxwriter       : None
lxml.etree       : 4.9.3
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 3.1.2
IPython          : 8.14.0
pandas_datareader: 0.10.0
bs4              : 4.12.2
bottleneck       : None
brotli           : 
fastparquet      : None
fsspec           : 2023.6.0
gcsfs            : 2023.6.0
matplotlib       : 3.7.2
numba            : 0.57.1
numexpr          : 2.8.4
odfpy            : None
openpyxl         : 3.1.2
pandas_gbq       : None
pyarrow          : 9.0.0
pyreadstat       : None
pyxlsb           : None
s3fs             : 2023.6.0
scipy            : 1.7.3
snappy           : None
sqlalchemy       : 2.0.17
tables           : 3.8.0
tabulate         : 0.9.0
xarray           : 2023.6.0
xlrd             : None
xlwt             : None
zstandard        : 0.19.0
tzdata           : 2023.3

</details>

[jbrockmendel]

while for exemple the numpy log

np.log is a ufunc, which pandas is able to affect the behavior of via __array_ufunc__. np.nan_to_num uses array_function_dispatch, meaning to handle this on our end would require implementing __array_function__. We have tried implementing that and stalled out, largely bc it is impossible to implement piece-by-piece (xref numpy/numpy#20044 (comment)). Until that changes, I don't expect this to be addressed within pandas.