BUG: groupby(Grouper) with all-NaT grouping keys
### 

- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.

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


### Reproducible Example

```python
import pandas as pd

df = pd.DataFrame({"date": [pd.NaT], "value": [11]})
grouper = pd.Grouper(freq="M", key="date")

>>> gb = df.groupby(grouper)
[...]
  File "pandas/core/resample.py", line 1878, in _get_timestamp_range_edges
    first = first.normalize()
AttributeError: 'NaTType' object has no attribute 'normalize'
```
```


### Issue Description

Example derived from test_timegrouper_apply_return_type_series


### Expected Behavior

Either not raise or raise at construction of the Grouper object with a useful exception message.

### Installed Versions

master