ENH: maybe_convert_objects seen NaT speed-up
I believe after `seen.object_ = 1` here:
https://github.com/pandas-dev/pandas/blob/c64c9cb44222a42f7b02d4d6007919cd0645f1be/pandas/_libs/lib.pyx#L1956-L1958
should go `break` as well.

Test:
```python
size = 10**7
arr = list(range(size))
arr[0] = pd.NaT
arr = np.array(arr)
```
```python
%timeit lib.maybe_convert_objects(arr, convert_datetime=0, convert_timedelta=0)
```
As now output is:
```python
1.84 s ± 14.3 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
```
With `break`:
```python
57.1 µs ± 887 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)
```
And both cases produce same array:
```python
array([NaT, 1, 2, ..., 9999997, 9999998, 9999999], dtype=object)
```