BUG: bug in DataFrame.groupby(Grouper) triggers a ValueError exception in cython generate_bins_dt64() code
### 

- [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
import numpy as np
index=pd.date_range('2019-12-31T00:10:00', '2020-01-31T00:10:00', freq='1T')
df = pd.DataFrame(np.zeros(len(index)), index=index)
grouper = pd.Grouper(freq='2D', closed='right')
sampled = df.groupby(grouper).sum()
```


### Issue Description

The _**groupby()**_ call creates a new Resampler object which builds the bins calling the _**_get_times_bins()**_ function.
This function detects the first/last entries using the origin and the close semantic and calls the **_date_range()_** helper to get the bins intervals which, in our example, are the following: 

```
DatetimeIndex(['2019-12-31',` '2020-01-02', '2020-01-04', '2020-01-06',
               '2020-01-08', '2020-01-10', '2020-01-12', '2020-01-14',
               '2020-01-16', '2020-01-18', '2020-01-20', '2020-01-22',
               '2020-01-24', '2020-01-26', '2020-01-28', '2020-01-30',
               '2020-02-01'],
              dtype='datetime64[ns]', freq='2D')
```
at this point the function calls into  **_self._adjust_bin_edges(self, binner, ax_values)_** passing the bins and the actual source values.

```
def _adjust_bin_edges(self, binner, ax_values):
    # Some hacks for > daily data, see #1471, #1458, #1483

    if self.freq != "D" and is_superperiod(self.freq, "D"):
        if self.closed == "right":
            # GH 21459, GH 9119: Adjust the bins relative to the wall time
            bin_edges = binner.tz_localize(None)
            bin_edges = bin_edges + timedelta(1) - Nano(1)
            bin_edges = bin_edges.tz_localize(binner.tz).asi8
        else:
            bin_edges = binner.asi8

        # intraday values on last day
        if bin_edges[-2] > ax_values.max():
            bin_edges = bin_edges[:-1]
            binner = binner[:-1]
    else:
        bin_edges = binner.asi8
    return binner, bin_edges 
```       

which seems to have some old spaghetti-code which tries to fix old issues...

if the frequency is not a single Day (???) (like in our example **freq='2D'**) and **_is_superperiod()_**  function (which seems broken given that it checks only the base/role frequency instead of the whole one: aka it can't detect that 2D is not a superperiod of D or that 48H is semantically the same as 2D.. etc...) returns True the code enters this code segment which adds to every bin interval a whole day without the last nanosecond transforming the first entry into something like this: 

```
DatetimeIndex(['2019-12-31 23:59:59.999999999',
               '2020-01-02 23:59:59.999999999',
               '2020-01-04 23:59:59.999999999',
               ...
               ...
               '2020-02-01 23:59:59.999999999'],
              dtype='datetime64[ns]', freq='2D')
```

which is totally nonsense given that the code later calls the generic cython **_lib.generate_bins_dt64()_** which compares the actual entries starting from **_'2019-12-31T00:10:00'_** to the first bin entry which is now a new 'edged' value **_'2019-12-31 23:59:59.999999999'_**. This in turn triggers the first sanity check since the first bin value is in the future in respect to the first value: 

```
@cython.boundscheck(False)
@cython.wraparound(False)
def generate_bins_dt64(ndarray[int64_t] values, const int64_t[:] binner,
                       object closed='left', bint hasnans=False):

    ...
    ...

    # check binner fits data
    if values[0] < binner[0]:
        raise ValueError("Values falls before first bin")

```



### Expected Behavior

The groupby() function should return without any exception.

### Installed Versions

<details>

>>> pd.show_versions()

INSTALLED VERSIONS
------------------
commit           : 73c68257545b5f8530b7044f56647bd2db92e2ba
python           : 3.8.8.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.15.0-140-generic
Version          : #144~16.04.1-Ubuntu SMP Fri Mar 19 21:24:12 UTC 2021
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.3.3
numpy            : 1.21.2
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.0.1
setuptools       : 54.2.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.3
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None
>>> 


</details>
