BUG: fix DataFrame(data=[None, 1], dtype='timedelta64[ns]') raising ValueError
- [x] closes #60064(Replace xxxx with the GitHub issue number)
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.
- [x] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.

The problem comes from the branch `elif is_float_dtype(data.dtype):` in function `sequence_to_td64ns`.
https://github.com/pandas-dev/pandas/blob/68d9dcab5b543adb3bfe5b83563c61a9b8afae77/pandas/core/arrays/timedeltas.py#L1114
`data` here is a 2D `array([[nan], [ 1.]])`.
But `cast_from_unit_vectorized` only accepts 1D array as input, thus producing the "Buffer has wrong number of dimensions" error (see [issue](https://github.com/pandas-dev/pandas/issues/60064#issuecomment-2428159736)), if I understand correctly the code below:
https://github.com/pandas-dev/pandas/blob/68d9dcab5b543adb3bfe5b83563c61a9b8afae77/pandas/_libs/tslibs/conversion.pyx#L133-L147

I notice that other branches for other dtypes in `sequence_to_td64ns` can work with 2D array data, so come up with this quick fix.
 CI should be fixed now. Can you merge main. 
> CI should be fixed now. Can you merge main.

Thanks. I merged main and added in whatsnew. > But cast_from_unit_vectorized only accepts 1D array as input

My preference ideally would be to make cast_from_unit_vectorized correctly handle 2D inputs.  Handling it in _try_cast seems like a fine second-best. Merge when ready @rhshadrach  Friendly ping @rhshadrach  Thanks @yuanx749!