BUG: ArrowDtype.numpy_dtype returning ns units for non-nano timestamp and duration types
- [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).
- [x] 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/v2.1.0.rst` file if fixing a bug or adding a new feature.

`ArrowDtype.numpy_dtype` goes through the pyarrow `to_pandas_type` method which was added before pandas supported non-nano units. This PR ensures the correct units are passed along to the numpy dtype. This fixes 6 xfails.

pyarrow already preserves the units when going directly from pyarrow to numpy:
```
>>> import pyarrow as pa
>>> arr = pa.array([1, 2, 3], type=pa.duration("us"))
>>> arr.to_numpy()
array([1, 2, 3], dtype='timedelta64[us]')
```

thanks @lukemanley 