BUG: to_timedelta drops decimals from input if precision is greater than nanoseconds
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

I am trying to convert a time to timedelta. The input data is in string format. When number of decimals is too big, it resets all decimals to zero.

```python
import pandas as pd
d = {'Time':['8:53:08.26','8:53:08.71800000001', '8:53:09.729']}
df = pd.DataFrame(data=d)
pd.to_timedelta(df["Time"])
```
The result of the above pice of code gives:
```
0   0 days 08:53:08.260000
1          0 days 08:53:08
2   0 days 08:53:09.729000
Name: Time, dtype: timedelta64[ns]
```

As it can be seen, all the decimals from second data is lost.

#### Problem description

With the present behavior, a sorted array of data returns a wrong and unsorted array.

#### Expected Output
```
0   0 days 08:53:08.260000
1   0 days 08:53:08.718000
2   0 days 08:53:09.729000
Name: Time, dtype: timedelta64[ns]
```

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : f2ca0a2665b2d169c97de87b8e778dbed86aea07
python           : 3.8.5.final.0
python-bits      : 64
OS               : Windows
OS-release       : 7
Version          : 6.1.7601
machine          : AMD64
processor        : Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : es_ES.cp1252

pandas           : 1.1.1
numpy            : 1.19.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.2
setuptools       : 49.6.0.post20200925

</details>
