PERF: Improve performance for pyarrow to_numpy with na and na_value
- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [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
- [ ] 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.
- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.

saw this in the engine pr, avoids a warning and improves performance:

```
pr
%timeit ser.to_numpy(dtype="int64", na_value=1.5)
1.67 ms ± 11.2 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)

main
%timeit ser.to_numpy(dtype="int64", na_value=1.5)
/Users/patrick/PycharmProjects/pandas/pandas/core/arrays/arrow/array.py:893: RuntimeWarning: invalid value encountered in cast
  result = np.asarray(self._data, dtype=dtype)
2.42 ms ± 30.3 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
```
greenish